docs: def describe(feed: "Feed", sample_date: Optional[str] = None) -> DataFrame:
      """
      Return a DataFrame of various feed indicators and values,
      e.g. number of routes.
      Specialize some those indicators to the given sample date,
      e.g. number of routes active on the date.
  
      Parameters
      ----------
      feed : Feed
      sample_date : string
          YYYYMMDD date string specifying the date to compute sample
          stats; defaults to the first Thursday of the Feed's period
  
      Returns
      -------
      DataFrame
          The columns are
  
          - ``'indicator'``: string; name of an indicator, e.g. 'num_routes'
          - ``'value'``: value of the indicator, e.g. 27
  
      """
      from . import calendar as cl
  
      d = OrderedDict()
      dates = cl.get_dates(feed)
      d["agencies"] = feed.agency["agency_name"].tolist()
      d["timezone"] = feed.agency["agency_timezone"].iat[0]
      d["start_date"] = dates[0]
      d["end_date"] = dates[-1]
      d["num_routes"] = feed.routes.shape[0]
      d["num_trips"] = feed.trips.shape[0]
      d["num_stops"] = feed.stops.shape[0]
      if feed.shapes is not None:
          d["num_shapes"] = feed.shapes["shape_id"].nunique()
      else:
          d["num_shapes"] = 0
  
      if sample_date is None or sample_date not in feed.get_dates():
          sample_date = cl.get_first_week(feed)[3]
      d["sample_date"] = sample_date
      d["num_routes_active_on_sample_date"] = feed.get_routes(sample_date).shape[
          0
      ]
      trips = feed.get_trips(sample_date)
      d["num_trips_active_on_sample_date"] = trips.shape[0]
      d["num_stops_active_on_sample_date"] = feed.get_stops(sample_date).shape[0]
      f = pd.DataFrame(list(d.items()), columns=["indicator", "value"])
  
      return f